Table of Contents

• What is PEM?
• Overview
• Installation
• Usage
  • Executable
  • Library
  • Telegram Bot
  • Try OPEM in Your Browser!
  • MATLAB
• Issues & Bug Reports
• Contribution
• Outputs
• Thanks
• Reference
• Cite
• Authors
• License
• Show Your Support
• Changelog
• Code of Conduct

Overview

Usage

Executable

• Open CMD (Windows) or Terminal (UNIX)

• Run opem or python -m opem (or run OPEM.exe)

• Enter PEM cell parameters (or run standard test vectors)

  1. Amphlett Static Model

  2. Larminie-Dicks Static Model

  3. Chamberline-Kim Static Model

  4. Padulles Dynamic Model I

  5. Padulles Dynamic Model II

  6. Padulles-Hauer Dynamic Model

  7. Padulles-Amphlett Dynamic Model

  8. Chakraborty Dynamic Model

  • Find your reports in Model_Name folder

  Screen Record

Library

1. Amphlett Static Model

   >>> from opem.Static.Amphlett import Static_Analysis
   >>> Test_Vector={"T": 343.15,"PH2": 1,"PO2": 1,"i-start": 0,"i-stop": 75,"i-step": 0.1,"A": 50.6,"l": 0.0178,"lambda": 23,"N": 1,"R": 0,"JMax": 1.5,"Name": "Amphlett_Test"}
   >>> data=Static_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

2. Larminie-Dicks Static Model

   >>> from opem.Static.Larminie_Dicks import Static_Analysis
   >>> Test_Vector = {"A": 0.06,"E0": 1.178,"T": 328.15,"RM": 0.0018,"i_0": 0.00654,"i_L": 100.0,"i_n": 0.23,"N": 23,"i-start": 0.1,"i-stop": 98,"i-step": 0.1,"Name": "Larminiee_Test"}
   >>> data=Static_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

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3. Chamberline-Kim Static Model

   >>> from opem.Static.Chamberline_Kim import Static_Analysis
   >>> Test_Vector = {"A": 50.0,"E0": 0.982,"b": 0.0689,"R": 0.328,"m": 0.000125,"n": 9.45,"N": 1,"i-start": 1,"i-stop": 42.5,"i-step": 0.1,"Name": "Chamberline_Test"}
   >>> data=Static_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

4. Padulles Dynamic Model I

   >>> from opem.Dynamic.Padulles1 import Dynamic_Analysis
   >>> Test_Vector = {"T": 343,"E0": 0.6,"N0": 88,"KO2": 0.0000211,"KH2": 0.0000422,"tH2": 3.37,"tO2": 6.74,"B": 0.04777,"C": 0.0136,"Rint": 0.00303,"rho": 1.168,"qH2": 0.0004,"i-start": 0,"i-stop": 100,"i-step": 0.1,"Name": "PadullesI_Test"}
   >>> data=Dynamic_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

5. Padulles Dynamic Model II

   >>> from opem.Dynamic.Padulles2 import Dynamic_Analysis
   >>> Test_Vector = {"T": 343,"E0": 0.6,"N0": 5,"KO2": 0.0000211,"KH2": 0.0000422,"KH2O": 0.000007716,"tH2": 3.37,"tO2": 6.74,"tH2O": 18.418,"B": 0.04777,"C": 0.0136,"Rint": 0.00303,"rho": 1.168,"qH2": 0.0004,"i-start": 0.1,"i-stop": 100,"i-step": 0.1,"Name": "Padulles2_Test"}
   >>> data=Dynamic_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

6. Padulles-Hauer Dynamic Model

   >>> from opem.Dynamic.Padulles_Hauer import Dynamic_Analysis
   >>> Test_Vector = {"T": 343,"E0": 0.6,"N0": 5,"KO2": 0.0000211,"KH2": 0.0000422,"KH2O": 0.000007716,"tH2": 3.37,"tO2": 6.74,"t1": 2,"t2": 2,"tH2O": 18.418,"B": 0.04777,"C": 0.0136,"Rint": 0.00303,"rho": 1.168,"qMethanol": 0.0002,"CV": 2,"i-start": 0.1,"i-stop": 100,"i-step": 0.1,"Name": "Padulles_Hauer_Test"}
   >>> data=Dynamic_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

7. Padulles-Amphlett Dynamic Model

   >>> from opem.Dynamic.Padulles_Amphlett import Dynamic_Analysis
   >>> Test_Vector = {"A": 50.6,"l": 0.0178,"lambda": 23,"JMax": 1.5,"T": 343,"N0": 5,"KO2": 0.0000211,"KH2": 0.0000422,"KH2O": 0.000007716,"tH2": 3.37,"tO2": 6.74,"t1": 2,"t2": 2,"tH2O": 18.418,"rho": 1.168,"qMethanol": 0.0002,"CV": 2,"i-start": 0.1,"i-stop": 75,"i-step": 0.1,"Name": "Padulles_Amphlett_Test"}
   >>> data=Dynamic_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

8. Chakraborty Dynamic Model

   >>> from opem.Dynamic.Chakraborty import Dynamic_Analysis
   >>> Test_Vector = {"T": 1273,"E0": 0.6,"u":0.8,"N0": 1,"R": 3.28125 * 10**(-3),"KH2O": 0.000281,"KH2": 0.000843,"KO2": 0.00252,"rho": 1.145,"i-start": 0.1,"i-stop": 300,"i-step": 0.1,"Name": "Chakraborty_Test"}
   >>> data=Dynamic_Analysis(InputMethod=Test_Vector,TestMode=True,PrintMode=False,ReportMode=False)
   

   • For more information about this model visit here

   Parameters

   1. TestMode : Active test mode and get/return data as dict, (Default : False)
   2. ReportMode : Generate reports(.csv,.opem,.html) and print result in console, (Default : True)
   3. PrintMode : Control printing in console, (Default : True)
   4. Folder : Reports folder, (Default : os.getcwd())

   Note

   • Return type : dict

Telegram Bot

• Send /start command to OPEM BOT
• Choose models from menu
• Send your test vector according to the template
• Download your results

Try OPEM in Your Browser!

OPEM can be used online in interactive Jupyter Notebooks via the Binder service! Try it out now! :

• Check .ipynb files in Documents folder
• Edit and execute each part of the notes, step by step from the top panel by run button
• For executing a complete simulation, you can edit Test_Vector in Full Run section

Issues & Bug Reports

Just fill an issue and describe it. We'll check it ASAP!
or send an email to [email protected].

You can also join our discord server

Outputs

1. HTML
2. CSV
3. OPEM

Thanks

• Chart.js
• PyInstaller
• Draw.io
• Zahra Mobasher (Logo design)

Reference

Cite

If you use OPEM in your research , please cite this paper :

Download OPEM.bib(BibTeX Format)

Show Your Support

Give a ⭐️ if this project helped you!

If you do like our project and we hope that you do, can you please support us? Our project is not and is never going to be working for profit. We need the money just so we can continue doing what we do ;-) .